Analytics Engineer (Business Intelligence)

TL;DR

Analytics Engineer (Business Intelligence): Responsible for transforming raw data into well-structured, analytics-ready datasets for BI teams and business stakeholders with an accent on designing, developing, and optimizing data models. Focus on improving data models, processing workflows, and overall infrastructure.

Location: Larnaca or Athens, Cyprus. Hybrid work model (up to 2 days working from home).

Company

hirify.global is an internationally acclaimed multi-asset broker, delivering cutting-edge trading tools, platforms, and conditions to traders worldwide.

What you will do

• Design, develop, and optimize data models to support analytics, reporting, and machine learning workflows.
• Utilize SQL and Python to clean, process, and analyze large datasets efficiently.
• Develop, optimize, and maintain ETL pipelines for seamless data extraction, transformation, and integration.
• Create interactive dashboards and visualizations in Power BI, incorporating KPIs, business calculations, and data aggregations.
• Ensure data governance, integrity, consistency and scalability to support data quality, security, and compliance across all models.
• Collaborate with data scientists, analysts, and business stakeholders to translate data insights into actionable business strategies.

Requirements

• University degree in Computer Science or Engineering, or a related field.
• Minimum of 3 years of experience in designing, developing, and implementing data solutions.
• Hands-on experience in ETL/ELT pipeline development, including workflow automation and orchestration tools.
• Solid SQL scripting skills and understanding of SQL Server performance optimization, including indexing and query tuning.
• Advanced knowledge of data modeling techniques (e.g., star and snowflake schemas) for BI applications.
• Excellent command of the English language.

Nice to have

• Previous experience in the FX industry.
• Practical experience migrating BI and data engineering solutions to cloud platforms such as Microsoft Fabric or Azure Data Services.
• Hands-on experience with PySpark notebooks for building scalable data pipelines and performing advanced data analytics.

Culture & Benefits

• Hybrid Work Model (up to 2 days working from home).
• 22 days of Annual Leave (reaching up to 30 days per year based on years’ service).
• Comprehensive Health & Life Insurance (from day one!).
• Friday afternoons off in Summer (July & August).
• Birthday Leave.